Nowadays, data is considered to be one of the most valuable resources in the world. Some data is viewed as strictly confidential, so it needs to be protected and secured. Therefore, data masking is becoming increasingly popular. Data anonymization is a concern for many global businesses, including the Libelle company, which provides numerous optimal algorithms for data anonymization in its Libelle DataMasking product. Due to the fact that the aforementioned solution is implemented on-premise, the idea is to utilise current algorithms and transfer the masking functionality to the cloud. The main goal here is to enable serverless data anonymization, while the ultimate objective is to develop a simple-to-use solution that allows users to enter certain data, send it, and receive anonymized data back. This was accomplished through the use of a serverless architecture and the Function-as-a-Service (FaaS) model. According to the serverless concept, the architecture is handled by a third party, leaving developers to focus solely on the product's functionality and logic. FaaS is primarily concerned with event-driven computing paradigms in which the entire application code is only run in response to requests – in this case, sending data for anonymization. As a result, the organization's energy and resources are conserved, allowing management and developers to concentrate on the product and profit strategy. There are several technologies for implementing FaaS solutions, with AWS Lambda serving as the primary technology in this ‘serverless-data-masking’ scenario.